What investigators later uncovered was not a low-level operation but a digitally sophisticated trafficking enterprise. Behind the scenes, traffickers were using databases and custom-built software to market and manage prostitution “dates” by the tens of thousands. The resulting federal indictment documented 30,000 unique customer bookings—evidence of a high-volume, systemized network designed to hide exploitation in plain sight.
The case widened rapidly after a federal investigator turned to Marinus Analytics, a Pittsburgh-based technology company that builds artificial intelligence tools for counter-trafficking investigations, helping law enforcement identify and recover trafficking victims by organizing vast volumes of publicly available online content into leads investigators can act on.
Traffic Jam changes investigators’ workflow by extracting key information so time can be redirected toward field operations and victim support.
Marinus’ flagship platform, Traffic Jam, analyzes online data—commercial sex advertisements, images, descriptive labels—and cross-checks faces, tattoos, locations and timelines against law enforcement databases, including missing person records. In a digital marketplace saturated with millions of ads, shifting aliases and coded language, the system is designed to convert fragments of online noise into investigative patterns that can be acted on quickly, before delays compound the harm to victims.
Human trafficking remains a global crime with enormous human and financial impact, and the digital layer of modern exploitation—recruitment, advertising, control and monetization—creates both new dangers and new investigative leverage. As traffickers adopt automation, multilingual scams and synthetic media like deepfakes, counter-trafficking efforts are being pushed into an escalating technology contest in which innovation must advance alongside speed, clear safeguards, and human and institutional oversight.
In written testimony to the US House Subcommittee on Cybersecurity, Information Technology and Government Innovation on December 10, 2025, Marinus CEO and co-founder Cara Jones described the online commercial sex marketplace as a “vast ocean of data,” noting that investigators cannot manually track the volume of ads and related content. She argued that Traffic Jam changes investigators’ workflow by extracting key information so time can be redirected toward field operations and victim support.
Jones highlighted one capability as especially consequential: screening large numbers of missing person records. In two years, she wrote, the Traffic Jam platform analyzed 60,000 missing person records drawn from public sources and successfully identified 734 of them as victims being advertised for sexual services online. Ninety-five percent were girls and young women, and 84 percent were victims of color.
The claim is not that an algorithm “solves” trafficking but that it can analyze online ads and images quickly enough to flag potential victim matches.
The company’s model follows automated detection with human review—analysts and investigators who assess leads before action.
The broader counter-trafficking ecosystem is moving in the same direction: tools that fuse open-source intelligence, pattern detection and multilingual processing, while trying to keep humans in the loop. For example, The Exodus Road, a nonprofit that helps police locate survivors and arrest traffickers, has detailed how AI-enabled approaches combining online advertisements, social media indicators and other digital traces can support victim identification, reveal trafficking hotspots and enable investigators in different countries to coordinate transnational cases.
The stakes are high: The UN International Labour Organization’s latest estimates indicate roughly 27.6 million people were in forced labor in 2021, generating some $236 billion a year in illegal profits—figures that underscore the sheer scale of human exploitation markets and the financial incentives that drive criminal enterprises to continually adapt their methods.
Those adaptations are increasingly cyber-enabled, and they blur the line between trafficking and digital fraud. In its 2024 Global Report on Trafficking in Persons, the United Nations Office on Drugs and Crime (UNODC) notes that trafficking for exploitation in criminal activities has gained attention across the world, with detection rising over the past decade. The report’s Southeast Asia–focused section details “scam centers” where trafficking victims are confined and forced to run online fraud operations.
In some 25 countries, those victims are compelled to recruit targets through social platforms, build trust over time, and steer individuals toward fake investment opportunities designed to show fabricated returns—before locking them out of their accounts and cutting off access to their funds once money has been transferred.
The report flags the use of AI tools in such operations—generative AI for multilingual phishing, chatbots for manipulation, and deepfakes to defeat “know your client” checks required by financial and online platforms—alongside malware designed to evade security software. This dual-use reality is the central tension of the moment: The same technical capabilities that help investigators recognize patterns can also help traffickers industrialize deception.
Marinus’ message to lawmakers is that technology-driven intelligence is already changing what is possible in trafficking investigations. Such tools can trigger investigations even when victims are unable to ask for help, connect what appear to be isolated cases across jurisdictions, and support evidence-led prosecutions against networks that once operated largely beyond reach.
The next step is institutional—scaling tools that already work so they become standard across agencies, turning proven innovation into faster rescues, stronger cases and fewer victims left unseen.
